Moonshot AIKimi K2.6
Developed by Moonshot AI, Kimi K 2.6 is a native multimodal agentic model that excels in long-horizon coding, coding-driven design, and swarm-based task orchestration, with capabilities in transforming simple prompts into production-ready interfaces and workflows. Its Mixture-of-Experts (MoE) architecture, featuring 384 experts and a context window of 262,144 tokens, enables robust performance across various domains.
Input
Output
Context
262K
Max Output
33K
Parameters
1026.9B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Served variants
The same model in other encodings or serving configurations. Requesting moonshot-kimi-k2-6 lets routing pick among them; the ids below pin one build.
moonshot-kimi-k2-6:fp4quantized
Benchmarks
Estimated GPU requirements for Kimi K2.6
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Kimi K2.6
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Kimi K2.6 advertises a context window of 262,144 tokens, with a maximum output of 32,768 tokens in a single response. The figure is the creator's published maximum; a given provider may serve less, and the gateway routes on what each provider actually serves.
Yes. Kimi K2.6 is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Kimi K2.6 accepts Text and Image and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
Kimi K2.6 has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured Kimi K2.6 is shown as not available rather than estimated.
Yes. Kimi K2.6 is served on the managed pool through the OpenAI-compatible endpoint as moonshot-kimi-k2-6, pinned by name or chosen by routing when it is the best fit for a request. The Try in Playground button opens it directly.
About 988.2 GB at INT8 for the weights and a default context, from the catalog's 1026.9B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Oct 16, 2026
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